PSYCHOLOGY

The nature of Psychology

Psychology originates from two Greek words: psyche, meaning soul or mind; and logos meaning study or knowledge.

What is the definition of psychology?

Psychology is the scientific study of mental processes and behaviour in humans.

Mental processes generally refer to a person’s thoughts and feelings, which are personal, or subjective, and cannot be directly observed.

Behaviour refers to any externally expressed action made by a living person that can be directly observed.

These processes are interrelated and constantly interact.

Research Methods

What do you know?

1. What is the name given to the people involved in a research study?

2. An_______________ conducts an experiment

3. A _______________ is a testable predication about the relationship between two or more variables.

4. A ___________ is a portion of a larger group that is chosen to be studied for the research purposes.

5. The ___________ shows any affects of the IV.

6. In the _________ group, the IV is absent.

7. An ______________ variable is any other variable that may affect the results, other than the IV.

8. Drawing names out of a hat to decide who is to be involved in a research study is an example of a ____________ sample.

9. A _________ is a judgement about what the results of a study mean.

Answers1. Participants 9. Conclusion

2. Experimenter

3.Hypothesis

4. Sample

5. DV

6. Control

7. Extraneous

8. Random

Research Methods:

What are research methods?

A research method is a particular way of conducting a research study to collect accurate and reliable information about behaviour and mental processes.

Psychologists use a range of research methods and data collection techniques based on the scientific method.

Experimental Research

One of the most scientifically rigorous research methods used in psychology, as in other sciences, is the experimental method.

An experiment is used to test a cause-effect relationship between variables under controlled conditions.

Four different types of variables can be identified in an experiment. These are independent variables, dependent variables, extraneous variables and confounding variables.

Variables:

A variable is any factor that varies in amount or kind over time.

In a controlled experiment, the experimenter sets up variables and attempts to systematically control them in order to observe and measure what happens under those experiments.

IV and DV

Every experiment includes at least one independent and one dependent variable:

Independent Variable: The variable that is systematically manipulated, changed or varied in some way, by the experimenter (in order to assess its effect on the participants response).

The way in which the IV will be manipulated is planned and determined before the experiment begins.

It is called the ‘independent variable’ because the experimenter can independently vary it in some way.

Dependent variable: shows any affects of the independent variable. That is, the aspect of the participants behaviour or experience that is observed or measured and expected to change as a result of the manipulation of the independent variable.

It is called the ‘dependent variable’ because whether or not it will change and the way in which it will change depends on the effects of the Independent variable.

In terms of cause-effect relationship, the

Independent Dependent

variable variable

(CAUSE) (EFFECT)

EXAMPLE!

I am conducting an experiment. My hypothesis is:

That eating lollies before an exam will increase exam performance.

Ask yourself: What is being measured (what will change over the course of the experiment)?

Performance on the exam (mark/percentage etc.) (DV)

Ask yourself: What is causing the change is students’ exam results?

Consuming lollies before an exam vs not consuming lollies. (IV)

Experimental condition and control condition

In a simple experiment, the participants selected are allocated to one of two groups.

The experimental group is the condition in which the independent variable is present.

The control group is the condition in which the independent variable is absent.

The control group provides a standard against which the performance of the experimental group can be compared in order to determine whether the IV has caused some change in the behaviour or event being measured.

Experiments: How to conduct a study.

1. Clearly state the topic to be investigated.

2. Define key terms and how they will be measured.

3. Formulate a hypothesis.

Hypothesis:What is a hypothesis?

Educated guess about the relationship between two or more events.

Testable

Involves directional prediction (eg. More or less likely)

States the causal relationship between IV and DV.

REMEMBER: Your Hypothesis should always start with “That...” or “It can be hypothesised that…” It’s a statement about what you think will happen!

Example

I have developed a new theory. I think that the brighter colours I wear, the happier my year 12 students will be.

I want to develop a hypothesis on the experiment that is going to be conducted testing this theory. That is, a testable prediction about what the results might show.

HOW???What do I expect to happen?

Students happiness rating to increase.

What's going to cause students happiness ratings to change?

Colour of Miss Bowles' clothing (being either dark or light)

Dependent Variable

Lets put it all together:

That students happiness level will increase when Miss Bowles is wearing brighter clothing.

Independent

Variable

We need to know a little more detail…

Now that you are experts on writing hypothesis’, try adding in a few more details to write a research hypothesis.

Research HypothesisThe research hypothesis states the causal relationship between the IV and the DV to be tested; that is that the IV will cause the DV to change in a particular way.

It also shows how the variables to be tested are defined and stated in terms of how they will be observed, manipulated and measured.

Eg. Exercise (IV)- walking at a speed of 5km an hour for 15 minutes.

Depression (DV)- number of negative words written in a creative story

So….

Instead of simply writing- That exercise will decrease the risk of developing depression- we write…

That walking for 15 minutes a day at a pace of 5km an hour will decrease the risk of developing depression as measured by the number of negative words written in a creative story.

Operational Hypothesis:

An operational hypothesis gives us one more bit of info. It tells:

- how the variables will be observed, manipulated and measured

AND

-what the population is from which my sample has been selected?

So tell me…How have the variables been observed, manipulated and

measured?

- Exercise (IV)- walking at a speed of 5km an hour for 15 minutes.

- Depression (DV)- number of negative words written in a creative story

What is the population from which my sample has been selected?

- All students at Rosehill secondary college (population)

- Miss Bowles’ year 12 Psych class (sample)

Lets put it together:Experimental hypothesis: That walking decreases the risk of developing depression.

Research hypothesis:

+ walking at a pace of 5km an hour for 15 minutes everyday

+ number of negative words written in a creative story

(how its being measured)

OPERATIONAL HYPOTHESIS:

+ All students at Rosehill Secondary college

(population)

+Miss Bowles’ year 12 psych class

(sample)

= ????????????????????????????????

Lets put all together:

Operational Hypothesis: That students from Miss Bowles’ psychology class at Rosehill Secondary College will show that depression levels will decrease, measured by the number of negative words written in a creative story, as a result of walking for 15 minutes everyday at a pace of 5km an hour.

YOU as avid and enthusiastic psychology students have a theory that yelling out in class seems to increase your teachers annoyance. You are going to conduct an experiment on your theory and need to come up with an operational hypothesis..

Remember

Educated guess

Starts with ‘That..’

Enables us to tell what the IV and DV are

How have the results been measured?

What is the population from which the sample has been drawn?

Writing a research and operational hypothesis

1. Write an experimental hypothesis.

2. Identify the variables in the experimental hypothesis (IV and DV).

3. Describe how each variable will be measured in the study.

4. Replace the variables in step 2 with the variables in step 3 to form your research hypothesis.

5. Add population and sample for operational hypothesis.

Extraneous VariablesThere are many variables other than the IV that

might influence the DV in an experiment. Experimenters try to predict what these might be prior to an experiment and develop their research design to control, or minimise, the influence of as many of these unwanted or extraneous variables as possible.

An Extraneous Variable is a variable other than the IV that can cause a change in the DV in an experiment. When extraneous variables are present in an experiment, it is difficult to conclude with confidence that changes in the DV have occurred as a result of the IV and not some other variable.

They are usually identified at the beginning of the experiment so that they can then be controlled.

Confounding variables

A confounding variable is a variable other than the IV that has had an unwanted effect on the DV, making it impossible to determine which of the variables has produced the change in the DV.

The difference between a CV and an EV is that a CV causes a measurable change in the DV, whereas an EV may or may not effect the DV.

Identifying extraneous and potential confounding

variablesIndividual participant differences

Demand characteristics

Placebo effect

Experimenter effects

Order effects

Artificiality

Use of non-standardised instructions and procedures

Individual differences

The differences in personal characteristics and experiences of the individual participants in an experiment are commonly referred to as individual participant differences.

Eg. Age, sex, intelligence, personality, memory ability, education, ethnicity, motivation, mood, self-esteem etc.

These variables can effect a participants performance in an experiment.

The researcher will try to control these before they begin the experiment.

Demand characteristicsA demand characteristic is a cue expressed by the researcher or present in some aspect of the research study that communicates the kind of response that is expected from participants and leads them to believe that the research study requires, or ‘demands’, that they respond in a particular way.

Demand characteristics guide or bias a participant’s behaviour in some way.

Responses are usually unconscious.

One reason that participants willingly do things in a study is because of social desirability; that is because of their desire to provide socially acceptable responses. They try to be ‘good’ so as not to ‘upset’ the experimenter.

Placebo effect

The placebo effect occurs when there is a change in the responses of participants due to their belief that they are receiving some kind of experimental treatment and they respond in accordance with that belief.

For example driving ability and alcohol consumption- acting like you are drunk to please the experimenter (also a demand characteristic), feeling like your driving should be impaired because you have consumed some alcohol.

Experimenter effects

Often the experimenters expectations and actions can unintentionally effect the participants responses.

An experimenter effect occurs when there is a change in a participant’s response due to the researcher’s expectations, biases or actions, rather than the effect of the IV.

Experimenter expectancy involves cues the researcher provides about the responses participants should give in the experiment.

A self-fulfilling prophecy occurs when the researcher obtains results that they expect to obtain due to cues they provide rather than the IV (eg. Facial expressions (smiling), tone of voice, mannerisms).

Experimenter bias involves unintentional biases in the collection and treatment of data. Eg, misread data, give unintentional assistance to participants, or misinterpret a participants verbal response.

Order effects

In some experiments participants are exposed to more than one treatment condition and they may be required to perform the same task more than once.

An order effect occurs when performance, as measured by the DV, is influenced by the specific order in which the conditions, treatments or tasks are presented. Performing one task affects the performance of the next task.

Practice effects are the influence on performance (the DV) that arises from practising a task.

Carry-over effects are the influence that a particular treatment or task has on performance in a subsequent treatment or task that follows it.

Artificiality

Psychologists often conduct experiments in laboratory settings, so that the environment and procedures can be controlled and responses can be recorded.

However the laboratory is an artificial setting.

Artificiality refers to the effects that laboratory based research can have in terms of its lack of realism and differences to real-life settings.

Use of non-standardised instructions and

proceduresThe instructions and procedures used by the researcher can also impact on how participants respond, and therefore the results.

When the research procedures are non-standardised this means that they are not uniform or the same for all participants.

Even small variations in procedures may affect participants’ responses, for example time of day or the instructions given to participants.

Read the following scenarios and identify the extraneous variable that has not been accounted for from the options below. Justify your answer.- Order effect- Placebo effect- Experimenter effect- Individual participant differences- Artificiality- Demand characteristics- Non- standardised instructions and procedures

Scenario 1

Maddi was conducting research investigating the effect of music on study. She gave her participants a list of names starting with ‘A’ and asked them to learn it in silence. After one minute they wrote down all the names they could recall. She then handed the same group of participants another list of names starting with ‘A’ and she played music while they were learning the names. After one minute they wrote down all the names they could recall.

Read the following scenarios and identify the extraneous variable that has not been accounted for from the options below. Justify your answer.- Order effect- Placebo effect- Experimenter effect- Individual participant differences- Artificiality- Demand characteristics- Non- standardised instructions and procedures

Scenario 2

A teacher decides to give students in half of his class a new ‘super drug’ he has discovered, which is intended to improve their intelligence. The students in the other half of the class are told they will receive no drug and will have to compete academically with the rest of the class as best they can.

Read the following scenarios and identify the extraneous variable that has not been accounted for from the options below. Justify your answer.- Order effect- Placebo effect- Experimenter effect- Individual participant differences- Artificiality- Demand characteristics- Non- standardised instructions and procedures

Scenario 3

Highvale Basketball Club is trying to test the effectiveness of a new training program on shooting accuracy. They put their 10 tallest players through the training program then asked them to shoot 100 balls from the 3-point line. Their 10 shortest players did not complete the training program but also shot 100 balls from the 3-point line. The shooting accuracy of both groups was then compared.

Read the following scenarios and identify the extraneous variable that has not been accounted for from the options below. Justify your answer. - Order effect- Placebo effect- Experimenter effect- Individual participant difference- Artificiality- Demand characteristics- Non- standardised instructions and procedures

Scenario 4

Peter is a university graduate researching whether caffeine can improve driving ability. He is hoping that this is the case so that he can write a thesis on it. Group A ingests caffeine before taking a simulated driving test, and group B does not ingest any caffeine before taking a simulated driving test. As members of group A are conducting their driving test, Peter actively encourages them. When members of group B conduct their test, Peter stands over them and points out their errors.

Ways of minimising extraneous and confounding variables

Minimising individual participant differences-

Participant selectionParticipant selection – the way participants are selected for a research study and how they are allocated to the groups in the study are important features of doing experimental research.

The process of selecting participants for a research study is called sampling.

A sample is a group that is a subset or portion of a larger group chosen to be studied for research purposes.

The term population is used in psychological research to describe the larger group from which a sample is drawn.

The sample should mirror or be representative of the entire population of interest.

In psychology the population does not refer to all the people in a particular country or to the whole human race. It refers to a particular group who has one or more characteristics in common eg. All VCE students, all females with schizophrenia etc.

Researchers draw a sample from a population appropriate for their hypothesis and attempt to generalise or apply the results obtained for the sample to the population from which the sample is drawn.

- Convenience sampling

- Random sampling

- Stratified sampling

- Stratified- random sampling

Convenience samplingConvenience sampling or opportunity sampling involves selecting participants who are readily available without any attempt to make the sample representative of the population.

In most cases, convenience sampling produces a biased sample because only those people available at the time and location of the study will have a chance at being included in the sample.

This means that the data obtained can, at times, be misleading and the results cannot be legitimately generalised to the population.

Random sampling

Random sampling is a sampling procedure that ensures every member of the population of research interest has an equal chance of being selected as a participant for a study.

This may be done by tossing a coin or by using a lottery method like choosing names out of a hat.

A table of random numbers ensures that all members of the population have an equal chance of being selected for the research purposes.

Stratified sampling

In some research studies it is important to ensure that particular groups in a population of interest are represented in their known proportions in that population.

Stratified sampling involves dividing the population to be sampled into distinct sub-groups, or strata, then selecting a separate sample from each stratum, in the same proportions as they occur in the target population.

Eg. Attitudes of Australian voters to asylum seekers.

Stratified-random sample

Stratified-random sampling involves identifying all of the people within each stratum of research interest, then randomly selecting samples of proportionate size from within each stratum.

This sampling procedure can be very time consuming and difficult to achieve so it is not often used.

Participant allocation

After participants have been selected for a research study they must be allocated to the groups that will be used in the experiment.

This process must also be completed systematically and ensure that the personal characteristics of the sample are as evenly spread across the experimental and control conditions of the experiment as possible.

Random allocation

In random allocation participants selected for the experiment are as likely to be in one group as the other.

Random allocation can be achieved by flipping a coin, drawing names out of a hat, or using some other kind of lottery method.

The purpose is to evenly allocate participants to either group before the IV is introduced.

Minimising the order effect-

CounterbalancingA counterbalancing procedure is commonly used to control or minimise order effects such as practise and carry-over.

Counterbalancing involves systematically changing the order of treatments or tasks for participants in a ‘balanced’ way to ‘counter’ the biasing influence or unwanted effects on performance of any one order.

Between-groups counterbalancing involves counterbalancing the order in which the groups of participants are exposed to the experimental conditions.

Each group of participants receives the treatments in a different order.

Eg. If there were 20 participants in the alcohol and driving experiment, counterbalancing would require half the participants to undertake the driver test in the no alcohol condition first, followed by the driver test in the alcohol condition.

The other group would do the opposite.

The results are combined to achieve counterbalancing.

Within-groups counterbalancing requires each participant to be exposed to the same combination of conditions.

This means that each participant is exposed to the treatment conditions in one order and then again in the reverse order.

Minimising demand characteristics and

experimenter effects- Single and double blind proceduresA single-blind procedure describes a situation where the participants are not aware of the condition of the experiment to which they have been allocated and therefore the experimental treatment (the IV).

A double-blind procedure is where neither the participants or the researcher directly involved with the participants are aware of the conditions to which the participants have been allocated.

Minimising demand characteristics-

PlacebosIn order to control demand characteristics associated with the experimental group (as they are the one exposed to the IV) experimenter may use a placebo.

A placebo is a fake treatment which ensures that both groups experience the same demand characteristics of the experimental group.

In the alcohol experiment the control group would be given a substance that smells and tastes like alcohol but is not alcoholic and therefore would eliminate all demand characteristics.

Minimising the effects of non-standardised procedures-

Standardised instructions and procedures

The use of standardised instructions means that the instructions given to all participants for each condition should be predetermined and identical in terms of what they state and how they are administered.

Researchers usually read from a script to do this.

It is also essential that all participants are exposed to the same environment and procedures, with the only exception being exposure to the independent variable.

Standardised procedures are the techniques used for making observations and measuring responses identical for all individual participants and ensuring they are all treated in the same way, as appropriate to the experimental condition.

3 types of experimental

designs. What are they??

What are the 3 types of experimental designs?

1. Repeated measures design: Participants participate in both the control and experimental conditions.

ADVANTAGE:

-no individual differences between participants.

DISADVANTAGE:

-repetition effects: May hinder performance on 2nd condition due to boredom, or increase performance due to practice effects. Can be overcome by counterbalancing: reversing the order of presentation for half the participants.

2. Matched-Participants design: control is achieved by matching participants on relevant characteristics eg. Intelligence, age, gender and then allocating to each condition.

ADVANTAGE:

-Subject variables are kept constant and so will not have a confounding effect on research.

DISADVANTAGE:

-Subjects may never be perfectly matched.

-Matching is time consuming.

3. Independent-Groups design: participants are randomly allocated to groups and it is assumed relevant characteristics are balanced between groups.

ADVANTAGE:

-Random allocation controls extraneous variables as participants are as likely to be in either condition.

-Order effects and demand characteristics (fatigue) are likely to be eliminated as participants only participant in 1 condition.

DISADVANTAGE:

-Despite random allocation, subject variables can still occur and have an unwanted effect on research.

Data CollectionAll psychological research involves the collection of information.

Information may be collected through:

- Case studies

- Naturalistic observation

- Self-reports

- Questionnaires

- Interviews

- Experiments.

In research, the information which is collected is called data. The data may be considered as ‘evidence’ that will form the results of the study and be the basis of the conclusions that will be made.

DataThere are two different data types- quantitative and

qualitative data.

Qualitative data is information about the ‘qualities’ or characteristics of what is being studied.

Examples of qualitative data are:

- descriptions, words, meanings, pictures, texts…

Qualitative data can describe any aspect of a person’s mental experiences or behaviour, what something is like, or how something is experienced.

Quality is a key word to remember.

DataQuantitative data is numerical information on the

‘quantity’ or amount of what is being studied; that is, how much of something there is.

It may be raw data that has not been analysed in any way, such as lengths or weights, percentages, mean reaction time and so on.

The majority of psychological studies that we will be looking at will refer to quantitative data more that qualitative data.

The use of numerical data makes it easier to summarise and interpret information collected through research. This is why quantitative data is often preferred over qualitative data.

Making sense of dataWhen research has been conducted and results obtained,

researchers generally do three things:

1. The results are summarised and described so that they can be interpreted.

2. Then they are interpreted so that they can be understood.

3. Then the results are explained; that is what do the results mean.

Researchers use statistics to summarise and interpret the results obtained from research.

Statistics are essentially mathematical procedures.

Two main kinds of statistics:

-Descriptive and Inferential

Descriptive StatisticsResearchers use descriptive statistics to

organise, summarise, and describe the data so that it can be interpreted.

Data can be summarised and presented in a table for example.

To enable data to be compared, a number that summarises the data could be calculated. This could be the mean (which is the average of all the scores), it could be how spread out (how variable) from the mean score the individual scores are for a particular group, or we could use visual representations of the results eg. Frequency distributions or histograms.

Inferential StatisticsDescriptive statistics are very useful for summarising data, but

they do not in themselves indicate whether the results are meaningful, whether the hypothesis being tested is supported.

Inferential Statistics involve mathematical calculations using the data to enable researchers to infer, or draw conclusions, from the results.

When results have been obtained from a sample, inferential statistics are used to help decide whether these results would occur in the population.

Inferential statistics can also be used to provide information about whether the results are statistically significant; that is how likely it is that the results are due to the effects being tested or whether they are more likely to be caused by chance factors.

How do we decide whether the results from a study have been caused by the IV?

We conduct a test of statistical significance!

The term statistical significance is used to indicate whether the difference in the results obtained for the experimental and control groups in an experiment is a ‘real’ difference due to the IV, and not due to chance factors alone.

If the likelihood that the results occurred by chance is LOW, we can say the results are ‘statistically significant’.

One way to work this out is to repeat the experiment several times in exactly the same way with exactly the same participants to see whether the same results are obtained.

Tests of significance eliminate this time consuming procedure and can determine the extent to which chance operated and whether it is at an acceptable level.

The significance level of any difference is called a p value with p standing for probability.

An acceptable p value is established before a study is conducted.

p values

A true difference can be said to be due to the IV when the probability that it might be due to chance is 5 or fewer times in 100 repetitions of the study.

Results are significant at the 0.05 level.

Significance level= p value (probability)

So what does all this mean?

You need to know…

A result that could have occurred by chance 5 times or less out of 100 (i.e. p<0.05) is generally considered significant; ie a reliable difference NOT due to chance.

A test of significance for research investigating a link between memory decline

and age was found to be p<0.02.

This means that the probability that the results occurred due to chance is ………………………………………….

This means that:

The results are statistically significant

The results are not statistically significant

The IV has caused a change in the DV

The IV has not caused a change in the DV; chance factors have caused the change

A conclusion can be drawn

A conclusion cannot be drawn

A test of significance for research investigating a link between a reduction in

concentration levels when listening to music was found to be p>0.05.

This means that the probability that the results occurred due to chance is ………………………………………….

This means that:

The results are statistically significant

The results are not statistically significant

The IV has caused a change in the DV

The IV has not caused a change in the DV; chance factors have caused the change

A conclusion can be drawn

A conclusion cannot be drawn

A test of significance for research investigating the effect of caffeine drinks on

weight gain was found to be p>0.05.

This means that the probability that the results occurred due to chance is ………………………………………….

This means that:

The results are statistically significant

The results are not statistically significant

The IV has caused a change in the DV

The IV has not caused a change in the DV; chance factors have caused the change

A conclusion can be drawn

A conclusion cannot be drawn

Conclusions and generalisations

When a researcher has formed a view about the meaning of their results, a conclusion needs to be drawn from their results.

A conclusion is a decision or judgment about what the results obtained from an investigation mean.

The first type of conclusion relates to whether the hypothesis in an experiment is supported or rejected (it is never, however, proven).

The second type of conclusion is known as a generalisation.

A generalisation is a decision or judgement about how widely the findings of a study can be applied, particularly to other members of the population from which the sample was drawn.

Reliability and validity

Reliability refers to the consistency, dependability and stability of the results obtained from the study.

Eg. If you did the same experiment twice you should expect to get the same results each time.

At times, if the experiment is conducted with different participants, the researcher may obtain different results due to the differences in the participants, however, the results should still be similar.

Reliability and validity

Validity means that the research study has produced results that accurately measure the behavior or event that it claims to have measured.

Eg. A questionnaire about depression would be expected to measure depression- not anxiety or irritability.

A measurement tool has construct validity when there is evidence that the measured behaviours relate to the specific characteristic or behaviour being assessed. (That physical violence and verbal abuse are indicators of aggression).

External validity refers to how well the research findings can be generalised or applied beyond the specific participants and settings used in the study.

Ethics

The term ethics refers to standards that guide individuals to identify good, desirable or acceptable conduct.

Confidentiality- a participants right to privacy, meaning that in a study details about the participants identity cannot be revealed unless their written consent is obtained.

Voluntary participation- the researcher must try to ensure that participants’ involvement in the research is voluntary. Participants must not be put under any pressure to take part in the study.

Ethics

Informed consent- wherever possible participants must be appropriately informed of the nature and purpose of the investigation. This must be appropriately documented.

Withdrawal rights- The researcher must inform participants of the nature of the research and that they are free to participate or to decline to participate or to withdraw from the research.

Ethics

Deception- when it is necessary for scientific reasons to conduct a study without fully informing participants of its true purpose prior to commencement, the researcher must ensure that participants do not suffer distress from the research procedure.

Debriefing- The researcher must provide an opportunity for participants to obtain appropriate information about the nature, results and conclusion of the experiment.

Role of ethics committees

In universities, ethics committees review and assess proposals for research and monitor the conduct of the experimenter to ensure all ethical guidelines are adhered to. Their job involves:

1. Ensuring research is designed and conducted ethically

2. Ensuring the researcher is qualified and experienced

3. Monitoring any approved research

4. Handling complaints

5. Ensuring accountability of the researcher

Use of animals in research

Read over page 82 and 83 of your text book and complete questions 2 & 3 of LA 1.27.